/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://www.apache.org/licenses/LICENSE-2.0
 *  *
 *  *    Unless required by applicable law or agreed to in writing, software
 *  *    distributed under the License is distributed on an "AS IS" BASIS,
 *  *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  *    See the License for the specific language governing permissions and
 *  *    limitations under the License.
 *
 */

package org.deeplearning4j.datasets.iterator.impl;

import org.deeplearning4j.datasets.fetchers.IrisDataFetcher;
import org.deeplearning4j.datasets.iterator.BaseDatasetIterator;

public class IrisDataSetIterator extends BaseDatasetIterator {

	/**
	 * 
	 */
	private static final long serialVersionUID = -2022454995728680368L;

	/**
	 * IrisDataSetIterator handles
	 * traversing through the Iris Data Set.
	 * @see <a href="https://archive.ics.uci.edu/ml/datasets/Iris">https://archive.ics.uci.edu/ml/datasets/Iris</a>
	 * 
	 * 
	 * Typical usage of an iterator is akin to:
	 * 
	 * DataSetIterator iter = ..;
	 * 
	 * while(iter.hasNext()) {
	 *     DataSet d = iter.next();
	 *     //iterate network...
	 * }
	 * 
	 * 
	 * For custom numbers of examples/batch sizes you can call:
	 * 
	 * iter.next(num)
	 * 
	 * where num is the number of examples to fetch
	 * 
	 */
	public IrisDataSetIterator(int batch,int numExamples) {
		super(batch,numExamples,new IrisDataFetcher());
	}

	

}
